SBdecomp: Estimation of the Proportion of SB Explained by Confounders

Uses parametric and nonparametric methods to quantify the proportion of the estimated selection bias (SB) explained by each observed confounder when estimating propensity score weighted treatment effects. Parast, L and Griffin, BA (2020). "Quantifying the Bias due to Observed Individual Confounders in Causal Treatment Effect Estimates". Statistics in Medicine, In press (doi to be added when published).

Version: 1.0
Depends: R (≥ 3.5.0)
Imports: stats, twang, graphics, survey
Published: 2020-05-12
Author: Layla Parast
Maintainer: Layla Parast <parast at>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
CRAN checks: SBdecomp results


Reference manual: SBdecomp.pdf
Package source: SBdecomp_1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: SBdecomp_1.0.tgz, r-oldrel: SBdecomp_1.0.tgz


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